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Figure. Graphical abstract (LCS = low-cost sensors; Ref = reference; AQ = air quality; Met = meteorology; GAM = generalised additive model; RF = random forest; QRM = quantile regression model; NO 2 = nitrogen dioxide). Air quality is monitored before intervention, then the intervention is implemented, and finally air quality is monitored again, which is analysed and modelled employing different machine learning approaches. [Display omitted] In this paper, the impact of smart traffic interventions on air quality was assessed in Thatcham, West Berkshire, UK. The intervention linked NO 2 levels with the cycle time of the traffic lights. When NO 2 levels exceeded a certain threshold, the strategy was triggered, which reduced the traffic congestion by turning the traffic lights green. Eight Earthsense Zephyrs air quality sensors and nine inductive-loop traffic detectors were installed in Thatcham to simultaneously monitor the air quality and traffic flows, respectively. Compared to the pre-intervention period, the observed NO 2 concentrations decreased in June, July and August and increased in September 2021, however, this does not reveal the true effect of smart traffic intervention. Using the observed data on the days with- and without-exceedances, we developed two machine learning models to predict the Business-as-usual (BAU) air quality level, i.e., a generalised additive model for average concentration and a quantile regression model for peak concentration. Our results demonstrated that average predicted concentrations (BAU) were lower than the observed concentrations (with intervention) by 12.45 %. However, we found that peak concentrations decreased by 20.54 %. [ABSTRACT FROM AUTHOR]

This paper presents an integrated analysis of the costs and benefits of carefully constructed scenarios for the electrification of transport in Australia. Scenarios were constructed to responsively meet increased electricity demand, whilst maximising emission reduction, household finances and public health benefits. The scenarios bundle several technologies, including charging infrastructure, electric vehicles, home battery systems, and renewable energy. The fastest, mission-style, adoption scenario can reduce emissions by 9% of the 2030 carbon budget and reduce the loss of life by 24,000 by 2042. In all scenarios, government expenditure is dwarfed by the estimated public benefits, and households are nearly always better off in the medium to long term. Demonstrating the feasibility and advantages of surface transportation electrification in Australia, which presents cross-sections of rural and urban infrastructure, traffic and a large, socially and politically diverse population, provides broadly applicable evidence of the feasibility of electrification in other jurisdictions. [ABSTRACT FROM AUTHOR]

To contain the sudden spread of SARS-CoV-2, many governments encouraged people to work from home, generating an unprecedented diffusion of this activity. Furthermore, Covid-19 has induced drastic changes in everyday life and travel habits, which might persist in the future. This paper aims to understand and estimate the potential long-term impacts of telework on the environment due to the pandemic, by analyzing factors affecting the frequency of telecommuting, the mode choice for traveling to work, and pollutant emissions generated by these trips. Data from a mobility survey administered in Padova (Italy) was used. Results indicate that Covid-19 could cause a rebound effect reversing the positive impacts of working from home, since, even if the number of trips could be reduced, many shifts towards non-sustainable travel modes could occur. The promotion of telework should be combined with measures fostering sustainable travel habits to pave the way towards a future green mobility. [ABSTRACT FROM AUTHOR]

[Display omitted] A fuel cut-off injection strategy can be employed during deceleration to increase fuel efficiency, but NOx is immediately emitted after fuel injection recovery. In this paper, the NOx emissions under various driving cycles are investigated. The NOx mass emissions from gasoline vehicles with a fuel cut-off strategy measured are much higher than those without a cut-off. More comprehensive and aggressive tests were carried out to analyse NOx emissions. The total NOx emissions can be classified as associated with warming up, fuel cut-off and other. The proportion of fuel cut-off-caused NOx mass emissions was the highest (61.2%) in real driving emissions 1 (RDE1) owing to its aggressive driving and frequent pedal switching. In comparison, for Worldwide harmonized Light duty vehicle Test Cycle (WLTC) and Random Test Standardized aggressive (RTS-95), warming-up induced NOx dominates, followed by fuel cut-off and other, while for both RDE cycles, fuel cut-off is the primary factor. [ABSTRACT FROM AUTHOR]

[Display omitted] Exhaust gas recirculation (EGR) is a known method of reducing nitrogen oxides (NO X), but the impact of its deactivation on emissions has not been quantified. This paper, therefore, considers the impact of deactivating the EGR valve on NO X emissions in a diesel Euro 5 vehicle. The measurements were performed during nine driving cycles and in all cases, a significant increase in NO X emissions was found when the EGR valve was deactivated. NO X emissions increased between 176% and 407%, depending on the cycle driven. Measurement results indicate the origin of significant amounts of NO X emissions. Recommendations are to inform regulatory authorities about the effects of such manipulations in order to adopt more stringent measures and introduce them during periodic technical inspection of vehicles with the view to preventing such interventions. [ABSTRACT FROM AUTHOR]

Emissions from aviation contribute increasingly to both air pollution and climate change. Understanding how these emissions are distributed across regions, seasons, and different altitudes is important to fully ascertain the climate impacts caused by our current aviation sector and set a clear benchmark for our mitigation efforts. The Aviation Transport Emission Assessment Model (AviTEAM) is developed for this purpose. The model estimates various emission species from aviation activities based on flight trajectories, airplane, engine types, and atmospheric conditions. In this paper, we present the AviTEAM framework and apply it to study the emissions from commercial aviation in Norway. We find emissions associated with Norwegian air transport for 2019 of 4.5 Mt CO 2 , 26.2 ktNO x , 3.26 ktHC, and 1.8 ktCO. Furthermore, we exemplify how Automatic Dependent Surveillance-Broadcast data in combination with flight dynamic and emission models can be used to generate high-resolution geospatial emission datasets for research and national reporting purposes. • Provides an updated aviation emission inventory for Norway. • Uses Automatic Dependent Surveillance-Broadcast data for activity modeling. • Assesses each flight with aircraft type and engine-specific modeling. • Shows the distribution of fuel consumption and various emission species. • Concludes that the approach informs the scientific and other audiences. [ABSTRACT FROM AUTHOR]

[Display omitted] This paper assessed the impact of five different WMA additives categorized under organic, chemical and foaming-based technologies on the energy requirement and green house gas (GHG) emissions. The maximum bearable cost, corresponding to different additives, was determined to assess the optimal choice of warm mix technologies. Results demonstrated that the addition of WMA additives lowers the heat energy by 3–12% compared to HMA. Although diesel is the most expensive fuel (considered in this study), its use can offset the cost of additives, for some WMA additives, namely: SR0.7, C0.2, C0.35, and R0.4. Calculations indicated that among the various warm mix additives, Sasobit Redux produces least emissions, followed by Aspha-min, Rediset, Sasobit, Cecabase, and viscosity graded binder. It was concluded that the use of WMA technologies can provide possible cost savings, and reduction in GHG emissions. [ABSTRACT FROM AUTHOR]

• The top 5% of car users travel nearly 27,500 miles (4.8 times the average) and emit 5742 kg CO 2 annually (5.7 times the average). • The top 20% of car users in England travel 16,740 miles and emit 3200 kg CO 2 annually. • Male, high-income professionals and large car owners are more likely to record higher mileage. • Rationing the top 5% of car users would reduce emissions by 6.9% whilst rationing the top 20% would lead to reductions of 26%. • Rationing high CO2 emitters directly is more effective than rationing car mileage. This paper measures 'excess' car travel for its role in decarbonisation. On average, each English adult travels around 5,680 miles a year and emits 1,006 kg of CO 2. However, the top 5% 'excess' car users travel 4.8 times and emit 5.7 times the national average. Four binary logistic regression analyses were used to model the probability that people with specified characteristics belong to the 'excess' mileage and emitter groups. Results indicated that gender, employment and socio-economic status, household income (higher quintiles), company car availability, residential location and local population density were highly significant correlates of this 'excess' travel mileage. Multiple car ownership, business travel by car, multiple international flight frequencies and ownership of larger and diesel cars were positively associated with excess travel and emissions. A mileage rationing scheme targeting the top 20% users can cut emissions substantially (by 26%) compared to targeting 'excess' (top 5%) users only. [ABSTRACT FROM AUTHOR]

This paper examines the impact of geographical location on the energy consumption of double deck battery electric buses operating in four UK cities. By considering seasonal variation in ambient temperature and an assumed battery degradation process, the implications on operational cost and carbon emissions were investigated. Using a MATLAB/Simulink model the total energy demand of a vehicle operating on the UKBC was simulated. Energy consumption was combined with hourly seasonal averages of carbon intensity (gCO 2 /kWh) and wholesale electricity costs (£) to assess charging at different times of the day and year. At the beginning of life, the range could decrease by up to 17.3% due to heating load requirements. From beginning of life to end of life, range was predicted to decrease by up to 26%. Whilst the average operational costs are relatively consistent across the four regions, the average carbon emissions can be five times higher depending on location. [ABSTRACT FROM AUTHOR]

Few studies have analyzed the mobility impacts of TOD using a longitudinal research approach, and even fewer incorporated origin–destination (OD) information in the analysis. In this paper, we examine the impacts of a metro system with TOD features on the share of car and bus trips using Metro do Porto as a case study. The application of an autoregressive beta regression modeling approach to parish and OD data from two mobility surveys (2000 and 2017) allowed to detect changes in travel behavior accounting for pre-metro mode shares. Metro implementation was associated with strong reductions of the share of car trips in OD pairs with metro at both trip ends, especially when stations were TOD. Metro influence on the share of bus trips varied from neutral to positive, suggesting that bus and metro complement each other rather than compete for passengers. [ABSTRACT FROM AUTHOR]

New technological advances have made possible the recent development of automated and connected vehicles. However, there are still challenges to overcome. For example, maintaining constant values for speed and distance between vehicles when the connection has been interrupted. In this line of research, this paper presents the extension of the 3DCoAutosim simulation platform to integrate platooning by means of a dynamic-flexible model that we validate by creating use cases on traffic efficiency. We measured the effects of dynamic-flexible and consistent platooning on battery energy consumption taking into account real-world trips data, collected in Upper Austria. For this purpose we used three electric vans with an autonomous leader, a first semi-autonomous follower with driver and a last autonomous follower. The results showed that the proposed model is able to demonstrate a decrease of the total battery energy consumption when driving in platoon mode. • Connected semi-autonomous vehicles in platoon decrease battery energy consumption. • Dynamic-flexible platooning spontaneously reforms the platoon after a fragment. • Adaptive algorithms with the surrounding traffic increase the efficiency of transport. • Validated metamodel-based simulations represent real world systems. [ABSTRACT FROM AUTHOR]

• Existing researches on the impact of land use on trip generation has been explored. • Advanced data collection techniques for travel data collection were investigated. • Numerous approaches to trip generation modelling have been discussed. To assess the impact of any proposed development, it is necessary to estimate the trips that are likely to be generated because of such development. In case of developing countries, land use pattern varies significantly and it becomes very challenging to model the trip rates. In view of this, an effort has been made to synthesize the available literature related to modelling of trip generation rates. This paper provides a comprehensive review of studies related to impact of land use on trip rates, data collection techniques and modelling approaches. Major challenges associated with modelling of trip generation includes the unavailability of standard reference databases for multimodal trip generation, consideration of land use evolvement, less explored machine learning modelling approaches, and the feasibility of using emerging data collection techniques in travel surveys. Finally, a framework is proposed for modelling multimodal trip generation rates considering the above identified issues. [ABSTRACT FROM AUTHOR]

Transportation systems are fragile when facing various natural hazards. To analyze the performance of these systems under disruption, this paper provides a holistic multi-phase model to assess the resilience of a transportation system consisting of multiple modes. The hazard scenarios for modeling strikes of typhoons are generated by the Spatially Localized Failure (SLF) model and Monte Carlo simulation. Then based on the simulation of typhoon scenarios, we assess the resilience of both single-mode systems and a complementary system of multiple modes. This method is applied to the high-speed rail network and civil aviation network in China under different typhoon intensity scenarios. Results show the different resilience characteristics of the two networks, and more importantly unveil the complementary effect between the two modes when suffering from damages. The improvement of system resilience due to the complementary effects provides a motivation for promoting cooperation between high-speed rail and civil aviation. [ABSTRACT FROM AUTHOR]

• E-scooters' car-trip substitution potential for e-scooters estimated on basis of based on German mobility data. • 13 % of daily car trips or 2 % of vehicle-kilometers traveled suitable for replacement. • Calculation of daily potential greenhouse gas reduction through by switching to e-scooters. • Maximum savings of 1.2% of transportation GHG achievable if replacing gasoline cars. • Savings highly dependent on use case; potentially negative for BEV-replacement potentially negative. This paper explores which trips currently made in Germany by personal motorized transportation could be replaced by e-scooters and what effect this would have on greenhouse gas emissions. This potential for substitution is estimated on the basis of data from the national household travel survey in Germany. Our analysis shows that 13% of the daily car trips, corresponding to 2% of the car kilometers in Germany, are suitable for replacement. Based on these results, we show that saving potentials of greenhouse gas emissions are heavily dependent on the general conditions of the specific use case (e.g. e-scooter lifetime) and the type of vehicle replaced. At best, a saving potential of about 5.8 kt of CO 2eq per day could be achieved when trips with conventional cars are replaced by e-scooter driving. However, if battery electric cars are replaced, an increase in emissions may even occur under certain conditions. [ABSTRACT FROM AUTHOR]

When designing new electric vehicles for urban transport, both vehicle producers and operators need to establish and verify requirements that the vehicle has to fulfil regarding, e.g., energy storage capacity, driving range, or battery wear. These requirements are typically verified using simulation tools that concentrate mostly on electrical quantities, but disregard the influence of road infrastructure, surrounding traffic and detours. At the same time, an expansion of the electric vehicle fleet may have a negative impact on the existing power grid. Sufficient dimensioning of the grid elements and their verification are therefore necessary to keep the electric transport service reliable. This paper demonstrates a tool suitable for verification of battery-assisted trolleybus fleet and power infrastructure parameters, based on extensions to the SUMO traffic simulator. The tool carries out a joint simulation of electric and traffic-related quantities. It is demonstrated on seven use-cases inspired by real-life problems. • A tool to verify battery-assisted trolleybus fleet configuration is presented. • Includes fast DC power grid solver for electric grid analysis. • Combines traffic and electric circuit simulation to study mutual interactions. • The effect of surrounding traffic on vehicle power demands is considered. • Study of different parameters of a sample trolleybus network is presented. [ABSTRACT FROM AUTHOR]

Road traffic has changed as an essential source of influential urban air pollution in China. This study developed the Spatial Durbin Model to analyze the spatial spillover effects on air pollution caused by urban transportation infrastructure. The results show that high-emission areas congregate in the eastern region of China, which reflects noticeable spatial spillover effects and agglomeration characteristics as high-emission "clubs." When the traffic construction 1 1 Traffic construction area refer to the acreage of street area within the city in this paper. area increases by 1%, the air pollution level will increase 3.2% as accompanied. The improvement of the transportation infrastructure will bring out economic development. The speed of air pollution generated by the resources consumed by economic development is higher than that of technological improvement in the economic transition period to reduce air pollution. In contrast, economic growth and air pollution exacerbation represent a U-shaped curve connection. Most provinces remain in a stage where air pollution worsened with economic growth. [ABSTRACT FROM AUTHOR]

Privately-owned automated vehicles (PAVs) can relocate themselves elsewhere after arriving at destinations, thereby inducing empty vehicle mile traveled (VMT) and more greenhouse gas emissions. This paper examines travelers' preferences for PAV relocation, using stated preference surveys distributed in the Seattle and Kansas City regions in the U.S. Model results suggest that trip purpose, individual socio-economic and household characteristics, and local contexts influence PAV relocation decisions. Additionally, a willingness-to-relocate (WTR) metric is defined to represent how much time travelers would be willing to spend to relocate PAVs to save $1 in parking costs. The WTR estimates in both regions indicate the potential of induced VMT due to PAV parking relocation. Furthermore, travelers' awareness of fuel/energy costs associated with PAV relocation does not necessarily relate to a lower WTR, depending on the region. To curb excessive empty VMT from PAV relocation, explicit disincentives, such as a VMT fee, may be needed. [ABSTRACT FROM AUTHOR]

• Transition to fossil-free road transport by adopting EFVs. • Internal, external and governmental drivers for and barriers to EFV adoption. • Political ambivalence results in uncertainty over the future development of EFVs. • Developing a brand image as being a sustainable firm acts as a major driver for EFV adoption. • Grid uncertainties concerning capacity and ensuring sustainable energy production. Freight transport in urban areas needs to become more sustainable. There is much potential to reduce emissions by transitioning to electric freight vehicles (EFVs). The context of this study is Sweden, a country with ambitious goals for transitioning to fossil-free road transport that incentivizes the adoption of EFVs through regulations, subsidies and environmental zones. However, it seems that few companies are adopting EFVs. This paper aims to explore why that is by investigating drivers for and barriers to the adoption of EFVs. An embedded case study of five firms in Stockholm that are exploring the possibilities of using EFVs is conducted. The findings reveal a number of drivers and barriers, which are then categorized as internal, external or governmental. The results show uncertainties at the micro, meso and macro levels. Uncertainties relate to political and legal uncertainties, technological and infrastructure-related uncertainties, customer expectations and willingness to pay, and operational uncertainties. [ABSTRACT FROM AUTHOR]

[Display omitted] Identifying and evaluating railway noise sources is beneficial for establishing more targeted suppression and mitigation strategies. This paper proposes a novel approach to evaluate dominant railway noise sources for all bogie regions, by using an array of microphones and a physics-informed graph neural networks (GNN) model. The GNN model encodes not only the acoustic data collected by the microphone array but also the spatial relationship between noise sources and microphones, and it also considers the physical background of sound in terms of Doppler effect and acoustic attenuation. In-situ measurements of railway noises have been taken on an operating metro line to train and validate the GNN model which exhibits satisfactory performance in evaluating the noise sources of interest. The proposed approach enables a more flexible and cost-effective microphone array implementation strategy in comparison to the commonly adopted commercialized acoustic beamforming system. [ABSTRACT FROM AUTHOR]

This paper elucidates the association between built environments and motor vehicle emissions in small cities based on a geography weighted regression (GWR) model and multi-source fusion data from the urban area of Holingola, China. It finds that all emissions are spatially autocorrelated and spatially clustered throughout whole traffic analysis zones (TAZs). In addition, the GWR model bears more weight in measuring the local link when compared to the ordinary least squares model. What's more, the estimated coefficients of built environment characteristics vary positively or negatively in diverse TAZs. The findings demonstrate that the impact of built environment characteristics on motor vehicle emissions is significantly spatially heterogeneous. These results are not only conducive to a better comprehension of how built environment factors affect motor vehicle emissions, but also help to establish policies and strategies to promote energy conservation and emissions reduction in small cities. [ABSTRACT FROM AUTHOR]

School bus services play an important role in the daily commuting of students in small cities. In this paper, we research the school bus routing problem in Holingol, in which the accessibility of schools and the equity of schemes are considered. We measure the accessibility of schools by the average commuting time of students and the equity of schemes by the average detour time of students. The results show that applying the transfer strategy to solve the proposed problem can reduce the number of required school buses. Assigning more school buses to implement the second step of transfer strategy is conductive to improving the quality of solutions. Besides, the detour time for students is reduced to guarantee the equity of schemes. The findings highlight that policy makers should consider the long detour time of students and design schemes to overcome the observed inequity in small cities. [ABSTRACT FROM AUTHOR]

The potential for residents of smaller urban and rural areas to benefit from sustainable accessibility is an under-researched area. This paper explores accessibility to important every-day amenities within short travel times and how this differs across geography and mode of travel. The analysis draws on a combination of novel open-source data of the transport system and official Swedish register data of the total population of individuals and workplaces geocoded at a 100-meter resolution. The findings show considerable variation in accessibility to everyday amenities by travel mode for different settlement types. While the car provides good accessibility, short trips by bicycle are a very competitive alternative in urban and suburban areas. Access to every-day amenities by active travel modes is limited outside urban areas. Employing accessibility analysis by settlement type offers a powerful policy support tool for planners charged with developing measures to address sustainable accessibility for small urban and rural areas. [ABSTRACT FROM AUTHOR]

Traffic restrictions have received increasing attention in academia and are becoming a major measure to control urban air pollution. Many studies have evaluated the effects of such restrictions but have yielded mixed results. In this paper, 32 key cities in China are selected for comparative experiments. Cities that implemented traffic restriction policies are used as the experimental group, and other cities that did not implement traffic restrictions are regarded as the control group. First, based on a multi-period difference-in-difference model, we find that the implementation of traffic restriction policies improves urban air pollution. Second, we analyze the effect of only license-plate restrictions on air quality and discover that urban air pollution is still improved. Finally, we reveal that traffic restriction policies achieve different results in northern and southern Chinese cities. [ABSTRACT FROM AUTHOR]

• Truck-drone delivery system leads to significant emissions reductions compared to traditional delivery. • Automation positively affects the cost performance of the truck-drone delivery system. • Adverse wind condition impacts the delivery cost when human pilot is needed. Innovative solutions for last-mile delivery have sparked great interest among consumers and logistics operators. The combination of new technologies with existing ones can lead to new possible last-mile delivery configurations, among which truck-drone joint delivery is one of the most promising. This paper evaluates the environmental and economic sustainability of a last-mile delivery solution involving electric trucks equipped with drones, and it provides a comparison with traditional logistics systems. The comparative life cycle assessment methodology is used to quantify the greenhouse gas emissions per parcel delivered. The total cost of ownership methodology is adopted for the economic analysis. Results suggest that the truck-drone alternative leads to significant emissions reductions, while its cost performance is primarily affected by the drone automation level. [ABSTRACT FROM AUTHOR]

• A strategy for navigating heavy-duty trucks through communities is developed. • The strategy reduces community-wide exposure to truck's tailpipe emissions. • For one example community, low exposure route could be found in 23% of the trips. • On average, it would reduce PM2.5 and NOx inhalation by 50% and 50%, respectively. This paper describes a strategy for navigating a heavy-duty diesel truck through communities in a way that lowers the total exposure of community members to tailpipe emissions from the truck without significantly increasing travel time. This low exposure route was evaluated against the baseline route that truck drivers would normally take for a number of truck trips in two selected communities in Southern California. The evaluation results show that, for up to a quarter of the truck trips, it is possible to find a low exposure route that would reduce community-wide exposure to the truck's tailpipe emissions by up to 50% on average, with an average travel time increase of no more than 5%. These results demonstrate the potential of the exposure-based vehicle routing strategy to mitigate the air pollution impacts of diesel trucks in disadvantaged communities that are overburdened by truck traffic. [ABSTRACT FROM AUTHOR]

• A real option model is used to analyze investment in maritime hydrogen. • Scenarios are developed to account for fuel price differentials and policy measures. • A tax of at least 28% of fuel price is needed for a hydrogen-fueled ferry in 2025. • Favorable regulation increases the value of the option to invest now. • Taxation should be high to as soon as possible to avoid postponing investment. Alternative, and especially renewable, marine fuels are needed to reduce the environmental and climate impacts of the shipping sector. This paper investigates the business case for hydrogen as an alternative fuel in a new-built vessel utilizing fuel cells and liquefied hydrogen. A real option approach is used to model the optimal time and costs for investment, as well as the value of deferring an investment as a result of uncertainty. This model is then used to assess the impact of a carbon tax on a ship owner's investment decision. A low carbon tax results in ship owners deferring investments, which then slows the uptake of the technology. We recommend that policymakers set a high carbon tax at an early stage in order to help hydrogen compete with fossil fuels. A clear and timely policy design promotes further investments and accelerates the uptake of new technologies that can fulfill decarbonization targets. [ABSTRACT FROM AUTHOR]

Assessing the energy performances of a vehicle on the road requires collecting large data samples to ensure repeatability of the measurements despite the many variables which influence them. This paper proposes a method to dimension the campaign and compares various campaigns despite differences in the influencing variables through statistical analysis. This methodology has been applied to the Italian testing campaign of Toyota Yaris Hybrid 2020. The results are compared to those collected in a similar campaign for the previous model. The pandemic of COVID-19 forced the acquisitions to be made in months in which the weather and the traffic were different, and the reduced mobility lowered the traffic intensity. The proposed method was able to make the campaigns comparable besides the differences. It can also be applied to design future campaigns to reduce the quantity of collected data while maintaining the same statistical significance. The newest model of Toyota Yaris Hybrid performs better than the previous one, and it was analysed how. [ABSTRACT FROM AUTHOR]

• Analyses of the effects of improving public transport services on patronage. • Cases from eight Norwegian self-contained cities with 12,000–118,000 inhabitants. • Reorganised bus services into fewer, straighter, faster routes with higher frequency. • This resulted in patronage growth of 3.3–17.6% per year in the evaluation periods. • Clear goals and enhanced knowledge were key for successful interventions. • The results show that increased patronage can be achieved in smaller cities. The paper contributes to the scarce empirical knowledge concerning the effects of improving public transport services on patronage. It analyses cases in eight Norwegian cities, varying in size from 12,000 to 118,000 inhabitants, where bus services were reorganised into fewer, straighter, faster and simpler lines with higher frequencies. Walking distances to stops increased in some areas and services were reduced on less used routes. The interventions were followed by patronage growth of 3.3–17.6% per year over the evaluation period, contrasting the pre-change situation of lower growth or decline. Stronger focus on increasing public transport competitiveness versus cars, enhanced knowledge among planners and organisational changes leaving more power to the professionals stood out as important factors explaining why these interventions had been implemented. The results might be relevant for those involved in developing bus-based, regular, local public transport services for largely self-sustained small and medium-sized cities aiming at increasing patronage. [ABSTRACT FROM AUTHOR]

From an environmental equity perspective, the aim of this paper is twofold. First, we want to verify to what extent vulnerable population groups resided in areas exposed to high levels of aircraft noise before and during the COVID-19 pandemic (2019 and 2020) in the Montréal census metropolitan area. Second, we want to identify whether the use of an aircraft noise indicator rather than another generates significant variations in the results and consequently in terms of affected areas and populations. With the IMPACT web-application, we model aircraft noise contours from three cumulative (L den , L dn , L aeq ,24h) and a single-event (L Amax) metrics. The model's input data are retrieved by a website for flight tracking. Next, four variables are extracted from the 2016 Statistics Canada census at a fine scale level (dissemination areas): that is, the percentages of low-income individuals, visible minorities, children under 15 years old, and individuals aged 65 and over. The results show a significant drop in population exposed to aircraft noise in 2020 compared to 2019. In addition, the estimates of populations impacted by aircraft noise differ from one indicator to the next. The logistic regression models indicate that the inequities are inconsistent between cumulative and single-event metrics. [ABSTRACT FROM AUTHOR]

• Trips by dockless bike-sharing show the highest travel satisfaction. • The longer assess time is related to lower satisfaction with dockless bike-sharing. • Travelers have higher satisfaction with dockless bike-sharing as the primary mode. • Pro-public transit attitude relates to higher satisfaction of dockless bike-sharing. • Residential road network has no effect on satisfaction with dockless bike-sharinga. Using survey data collected among residents in Beijing, this paper presents an investigation of the difference in travel satisfaction between dockless bike-sharing and other travel modes. The effects of individual, spatial and trip attributes on travel satisfaction with dockless bike-sharing are also identified. Our analysis adds to the empirical support for higher satisfaction with trips by dockless bike-sharing than trips by private bicycles. The assess time for shared bicycles is negatively associated with travel satisfaction with dockless bike-sharing. In addition, travelers have higher satisfaction with dockless bike-sharing when used as the primary mode than as the first-mile/last-mile solution. Travel-related attitudes tend to play a more significant role in travel satisfaction with dockless bike-sharing than residential built environment. Travelers with a preference for bicycles and public transport and those who value the health or environmental influence of travel tend to evaluate dockless bike-sharing travel as more satisfying. [ABSTRACT FROM AUTHOR]

This paper develops an infrastructure-enabled eco-approach specifically for transit systems, where a two-stage simulation approach is proposed to include the impact of bus stops, and can further quantify the effects of infrastructure-enabled eco-approach on transit operating and service. The developed system is then embedded into a well-developed simulation environment, i.e., Simulation of Urban Mobility (SUMO), and a series of real-world-based cases are designed to compare the proposed system with traditional method and non-control case at segment-, line-, and network-level service respectively. Results reveal that the proposed method outperforms the traditional eco approach and can significantly improve the energy efficiency and reduce CO 2 emission by up to 54.33%, where the environmental benefits are more clearly seen when more transit services are involved. In particular, it has the capability of marginalizing the speed fluctuations around the bus stop. [ABSTRACT FROM AUTHOR]

Increasing commercial vehicles are equipped with automated driving features. Adaptive cruise control, a critical longitudinal control system of commercial automated vehicles (AVs), may have significant impacts on fuel consumption. To investigate the impacts, this paper collected high-resolution trajectory data of commercial AVs with different operating scenarios, speed ranges, and headway settings on the highway system. The AVs' fuel consumption was calculated by several state-of-the-art or classical vehicle fuel consumption models. From empirical analyses, we found that as the AV headway setting increases, the corresponding fuel consumption decreases. Also, we found that as the speed of AV traffic increases, the impacts of AV headway settings on fuel consumption decrease. Moreover, we compared the fuel consumption of AVs and human-driven vehicles (HVs). We found that for the same settings, the AVs always require less fuel consumption than the HVs. Following these findings, a set of managerial insights were provided into relevant stakeholders for future AV traffic. [ABSTRACT FROM AUTHOR]

Noise and greenhouse gas (GHG) emissions are two of the main externalities caused by road transport. At the EU and national levels, many efforts have been implemented to reduce them. Photovoltaic noise barriers (PVNBs) are a technical solution conceived for such a joint objective. This paper presents a method of calculating the efficiency of PVNBs through a cost-benefit analysis by considering current policies and comparing them with the 2010 benchmark scenario. The method was applied to a PVNB located along motorway A22 (Italy). Results show that the component associated with the reduction in transport externalities has been increasing compared with the incentives for electricity production. This outcome corresponds with EU policies but highlights the importance of interpreting results critically, an aspect that policymakers should be aware of in their evaluations. [ABSTRACT FROM AUTHOR]

• Assess the route redundancy of freeway networks in mega-city regions. • Propose diversity and dispersion of alternative paths as two complementary measures. • Assess route redundancy of mega-city freeway networks at network and city levels. • Consider three major mega-city regions of China in the case studies. In this paper, we investigate the performance of freeway networks in mega-city regions from the perspective of route redundancy—the provision of alternative routes for travelers when their primary routes are disrupted by disasters. Specifically, route redundancy is assessed with two complementary dimensions: the diversity and dispersion of alternative routes. The former represents the number of alternative routes without disruptions, and the latter reflects the robustness of this number during disruptions. Three typical mega-city regions in China, namely the Beijing-Tianjin-Hebei, the Guangdong-Hong Kong-Macao Greater Bay Area, and the Yangtze River Delta—are examined as case studies. Results indicate that travelers in first-tier cities (i.e., national economic or political centers) may have inadequate route redundancy. Route diversity increases when more topological cycles are traversed by numerous alternative routes. Additionally, alternative routes of the peripheral cities in mega-city regions are less dispersed, which cause their lack of redundancy and should be improved. [ABSTRACT FROM AUTHOR]

This paper performs a novel data-driven approach to optimize electric vehicle (EV) public charging. We translate the study area into a directed graph by partitioning it into discrete grids. A modified geographical PageRank (MGPR) model is developed to estimate EV charging demand, built upon trip origin–destination (OD) and social dimension features, and validated against real-world charging data. The results are fed into the capacitated maximal coverage location problem (CMCLP) model to optimize the spatial layout of public charging stations by maximizing their utilization. It is shown that MGPR can effectively quantify the EV charging demand with satisfactory accuracy. Optimized EV charging stations based on the CMCLP model can remedy the spatial mismatch between the EV demand and the existing charging station allocations. The developed methodological framework is highly generalizable and can be extended to other regions for EV charging demand estimation and optimal charging infrastructure siting. [ABSTRACT FROM AUTHOR]

Road grade is crucial in vehicle control and emission studies but challenging to obtain in large-scale road networks due to current methods' expensive deployment costs or limited accuracy. This paper proposed a scale-deployable and cost-efficient road grade estimation solution based on the fuel consumption rate (FCR) difference between flat and graded roads. Real-world road grades from design drawings and 261,814 second-by-second vehicle operating data from 680 light-duty vehicles were collected to examine the proposed method's performance. Sensitivity tests for vehicle types and sample sizes were conducted. Results show that (1) the proposed method acquired road grade with an accuracy of 0.12% mean absolute error (MAE), (2) in positive vehicle specific power (VSP) bins, a 1% road grade caused an average 16% FCR change, and (3) larger-scale fuel consumption data contributed to reducing estimation error which converged from 0.25% to 0.12% as the segment passes increased from 50 to 400. [ABSTRACT FROM AUTHOR]

This paper presents an important upgrade of a modelling tool devised by the authors for estimating aircraft noise around civil airports, which is based on a best-practice noise computation method and flight tracking data collected from the Internet and complemented by datasets of aircraft models, runways, and terrain elevation. Targeting more accurate noise predictions, the upgraded model introduces reasoned degrees of freedom in the standard flight procedures, and the tracked altitudes and speeds of each flight event are used to fit these modified procedures, which leads to an original mixed analysis-synthesis approach. Additional improvements include better runway assignment and consideration of actual weather conditions. Comparison of July 2019 results with official data for Heathrow, Gatwick and Schiphol airports shows an improved noise prediction, with an average underestimation lowered to 1.5 dB(A) for exposure-based metrics. Therefore, this upgraded modelling tool can be a reliable support to civil aviation authorities and policy-makers. [ABSTRACT FROM AUTHOR]

Improving community resilience relies on our ability to evaluate and understand the direct and indirect role of the transportation network. This requires losing our fixation with network functionality in favour of an approach that evaluates whether the network is truly serving the community's needs. In this paper, we present such an approach. With the understanding that sufficient and equitable access to amenities is key to community resilience, we leverage open-source data and routing algorithms to simulate road and service closures under various hazard scenarios. Among our methodological contributions is the ability to efficiently modify entire transportation networks to reflect hazard damage and identify isolated communities. This makes integrating hazard simulation with access and equity evaluations practicable on a large scale. We illustrate this approach in three cities. Ultimately, a broader view of the transportation network's role will better support communities prepare for and respond equitably when a disaster occurs. [Display omitted] [ABSTRACT FROM AUTHOR]

The pressure on shipping to reduce its carbon footprint is increasing. Various measures are being proposed at the International Maritime Organization (IMO), including Market-Based Measures (MBMs). This paper investigates the potential of a bunker levy in achieving short-term CO 2 emissions reductions. The analysis focuses on the tanker market and uses data from the latest IMO GHG studies and a variety of other sources. The connection between fuel prices and freight rates on the one hand and vessel speeds on the other is investigated for the period 2010–2018. A model to find a tanker's optimal laden and ballast speeds is also developed and applied to a variety of scenarios. Results show that a bunker levy, depending on the scenario, can lead to short-term CO 2 emissions reductions of up to 43%. Policy implications are also discussed, particularly vis-à-vis recent IMO and European Union (EU) action on MBMs. • Some properties of the tanker speed optimization problem are investigated. • We use data from GHG studies and several other sources to compute CO 2 emissions. • The link between speed and the ratio of spot rate by fuel price is investigated. • A bunker levy can reduce CO 2 emissions from tankers up to 43% in the short-term. • The IMO 50% GHG reduction target is unreachable via slow steaming induced by a levy. [ABSTRACT FROM AUTHOR]

The International Material Data System (IMDS) can be used as data source for life cycle assessments (LCAs) in the automotive industry. The level of data aggregation and degree of completeness affect precision of LCA results and required workload. This paper assesses this trade-off. Life cycle impact assessment scores for an engine, modelled as detailed as possible, were compared to results for seven simplified modelling options. The study concludes that: (1) employing IMDS data with lower resolution reduced the workload marginally; (2) cutting-off materials below 1 wt-% greatly decreased workload while maintaining reasonable precision; (3) decreasing the number of substances representing each material largely affected scores for most impact categories except a few, including the climate change category, while (4) excluding complementary data for manufacturing significantly impacted greenhouse gas emissions. Since modelling choices affect the impact categories differently, aligning choices with the purpose of the study and available workload is paramount. [ABSTRACT FROM AUTHOR]

Designing low-construction-emission cross-sections of mountainous highway alignments is challenging. To address this issue, this paper develops a framework of cross-section optimization for highway alignment (COHA) to minimize the construction costs and emissions of the mountainous highway. First, COHA enumerates the earthwork costs of all possible highway cross-section locations in each cross-section profile. Second, we classify cross-sections into two categories, sensitive and nonsensitive cross-sections, with stochastic dominance (SD) theory and a complete ranking method. Third, to obtain the final optimized highway alignment, the initial alignment determined by optimal cross-sections is fitted by the weighted least square method with two dimensions. Finally, this methodology is applied to a real-world case study in a mountainous region, and the results verify that COHA can automatically optimize highway alignment, decreasing carbon dioxide emissions and land use by 3.6 % and 3.1 %, respectively, compared with manual work. [ABSTRACT FROM AUTHOR]

• We identify the relationship between bike sharing and public transit (PT). • We estimate the environmental impacts of bikeshare as it also substitutes PT. • 27.9% of bikeshare trips substitute buses and 8.1% substitute subways. • Bikeshare has significant environmental benefits by replacing other modes. • Environmental benefits are overestimated if not considering the substitution for PT. Bike sharing has the potential to benefit the environment with less energy consumption and CO 2 emissions. Most previous studies on this topic assumed that bikeshare trips mainly substitute cars. However, bikeshare also replaces ecologically friendly transportation modes like public transit (PT). Therefore, it is vital to examine bikeshare's modal shift from PT to fully assess its environmental impacts. This paper examines the bikeshare and PT relationships in Chengdu,and environmental effects of bike sharing under two cases based on this relationship. The first case only considers the substitution of bikeshare for car and walking, and 19,964.31 L of fuel and 4125.13 kg of CO 2 can be saved; while the second case also considers its substitution for buses and subways, and 13,198.68 L of fuel and 2564.31 kg of CO 2 can be saved. Results indicate that the environmental benefits of bike sharing may be overestimated if not considering its substitution for PT. [ABSTRACT FROM AUTHOR]

• Data come from a survey of residents of Jacksonville, FL after Hurricane Matthew. • MNL models identify factors associated with accommodations and destinations. • Greater hurricane graphics understanding decreased the probability of staying in the area. • Greater certainty of hurricane impact location decreased the probability of going southeast. • Greater certainty of hurricane impact time increased the probability of staying in a home. This paper investigates how perceived certainty factors influenced households' selection of destination and accommodation type during evacuation. Using survey responses from Jacksonville, FL, multinomial logit models were developed for both choices. For the first, greater understanding of hurricane-related graphics decreased households' probability of staying within their community. Households with a member who has special medical needs and those evacuating with a greater number of vehicles were more likely to stay in the eastern portion of their county. Greater perceived certainty about the hurricane impact location decreased households' probability of evacuating to the south. For the accommodation model, married evacuees and those who received official evacuation notices had increased likelihood of staying in hotels/motels, while those who evacuated a day before landfall were less likely to do so. Greater perceived certainty about hurricane impact time and frequency of communication with social network members increased the probability of staying in a peer's home. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has induced significant transit ridership losses worldwide. This paper conducts a quantitative analysis to reveal contributing factors to such losses, using data from the Chicago Transit Authority's bus and rail systems before and after the COVID-19 outbreak. It builds a sequential statistical modeling framework that integrates a Bayesian structural time-series model, a dynamics model, and a series of linear regression models, to fit the ridership loss with pandemic evolution and regulatory events, and to quantify how the impacts of those factors depend on socio-demographic characteristics. Results reveal that, for both bus and rail, remote learning/working answers for the majority of ridership loss, and their impacts depend highly on socio-demographic characteristics. Findings from this study cast insights into future evolution of transit ridership as well as recovery campaigns in the post-pandemic era. [ABSTRACT FROM AUTHOR]

This paper contributes novel empirical and theoretical knowledge on how built environment characteristics affect travel behaviour in small and medium-sized cities and how this differs from larger cities. The competitiveness of sustainable modes versus the private car tends to increase and commuting distances tend to decrease with proximity of dwellings and workplaces to the city centre, following similar patterns as in larger cities, although the tendencies are weaker. Car-usage tend to decrease with higher city-level densities. Relatively dense mixed-use zones outside the inner-city generate higher car shares and longer commutes compared with inner cities and in some cases also outer parts of cities. It is concluded that small and medium-sized cities aiming at improving the competitiveness of sustainable modes versus the private car can follow the same advice as larger cities–steering new urban development to central parts of cities and avoiding new development in the outer areas. [ABSTRACT FROM AUTHOR]

Low-carbon travel for rural residents in China is of great significance for reducing CO 2 emissions and achieving the "dual carbon goals". This paper uses system dynamics modeling and case analysis to explore the realization path of low-carbon travel in rural China, establishes a complex system dynamics model of low-carbon rural travel in China. By running multi-scenario simulations, the characteristics of rural residents' travel and the trend of CO 2 emissions in China are found. Through the case study, it is found that the built environment, low-carbon travel policy, rural residents' travel preference and travel cost are the important factors affecting rural low-carbon travel. New energy policy can effectively reduce rural travel CO 2 emissions. However, an excessively large increase in rural low-carbon public transport would reduce marginal benefits. The government should choose the right policy intensity according to the economic and fiscal situation. [ABSTRACT FROM AUTHOR]

• Bike-sharing systems can contribute to transport justice. • These systems typically only target already mobile groups. • Stakeholders must prioritise equality objectives to promote transport justice. New mobility solutions have so far primarily been designed to meet the mobility needs of affluent user groups and have had limited impacts on objectives related to justice. This paper sheds light on a bike-sharing system implemented by a local authority in Sweden and discusses the findings in relation to the literature on transport justice. The study is based on a single case study and demonstrates that the system mainly attracts users who already have high accessibility. That docking stations were placed in low-income residential areas, combined with the fact that the price model was affordable, suggests that the system has potential to promote transport justice. The study indicates that this equality profile was primarily treated as an add-on in the design and setting up of the system. [ABSTRACT FROM AUTHOR]

Transportation is a basic social need, but most trips are done by private vehicles, which is not environmentally sustainable with growing urban populations. Micromobility (e.g., shared bikes) represents a significant opportunity to replace short private vehicles trips (0–3 miles) and reduce transportation sector emissions. This paper uses Seattle as a case study and estimates that up to 18% of short car trips could be replaced by micromobility. A static traffic assignment model is developed to simulate and compare the results of peak hour traffic under a base case scenario (2014 traffic conditions) to scenarios where a portion of short car trips are substituted by micromobility. Results indicate that micromobility could reduce congestion on heavily congested corridors and wide-scale bike lane deployment can maximize congestion benefits, but the impacts to energy use and emissions are disproportionately low and other measures (e.g., vehicle electrification) are needed to meet climate change emissions targets. [ABSTRACT FROM AUTHOR]

Sufficient accessibility to opportunities, with different transport modes, is an important factor in order to avoid transport-related social exclusion and transport poverty. This paper investigates the social and geographical disparities in accessibility and time competitiveness of public transport in the Oslo region. Both place-based access to employment opportunities and the working population's individual-specific commutes are measured. The study combines registry data with detailed accessibility metrics and uses descriptive maps and spatial regression models to study transport poverty. The results show that less affluent neighbourhoods suffer from low accessibility and poor time competitiveness of public transport, which is partly related to the suburbanization of poverty. This suggests that the transition to low emission mobility, with restrictions on car use, may be especially burdensome in less affluent neighbourhoods. The findings can help policy makers in securing an equitable transition from car to more sustainable transport modes. [ABSTRACT FROM AUTHOR]

• Analyses of four Norwegian self-contained cities with 28,000–1,020,000 inhabitants. • Surveys at public transport stops and of commuters. • Walking trips to local public transport stops last 4.1–6.0 min on average. • Walking trips to railway stations last 6.6–8.6 min on average. • Walking distances to local public transport increase with increasing city size. • Short walks increase the probability of using public transport for commutes. This paper contributes to the scarce empirical knowledge concerning distances and durations of walking trips to public transport in smaller cities and in European cities. Results show that walking trips to local public transport stops last 4.1–6.0 min (328–520 m), on average, in different cities, and walking trips to railway stations last 6.6–8.6 min (528–688 m). Walks are longer on the workplace side than on the home side of the journey. Walking distances to local public transport stops increase with city size. Short trips to stops increase the likelihood of using public transport for commutes. Survey results suggest that higher frequencies and direct connections are more important than shorter walks to stops to make more people commute by public transport in the smaller cities. The results may be relevant for smaller and larger cities aiming to improve public transport competitiveness versus the private car on commutes. [ABSTRACT FROM AUTHOR]